Title :
Improving N-Finder technique for extracting endmembers
Author :
Maghrbay, Mahmoud ; Ammar, Reda ; Rajasekaran, Sanguthevar
Author_Institution :
Comput. Sci. & Eng. Dept., Univ. of Connecticut, Storrs, CT, USA
Abstract :
N-FINDER algorithm is widely used for endmember extraction. One of the disadvantages of N- FINDER is that its implementations take long run time due to the relatively large computational complexity of N- FINDER. Successfully reducing the size of the input data set -the hyperspectral image that the algorithm works on can reduce the overall run time of the algorithm. A method for successfully selecting the proper sample of the data set to work on is provided in this paper. Using this reduction technique, a faster and statistically more accurate version of N-FINDER is presented.
Keywords :
computational complexity; data reduction; feature extraction; geophysical image processing; minerals; remote sensing; N-finder technique; computational complexity; endmember extraction; hyperspectral image; input data set size reduction; reduction technique; remote sensing; Bismuth; Endmember extraction; Hyperspectral images; N-FINDER algorithm;
Conference_Titel :
Signal Processing and Information Technology (ISSPIT), 2011 IEEE International Symposium on
Conference_Location :
Bilbao
Print_ISBN :
978-1-4673-0752-9
Electronic_ISBN :
978-1-4673-0751-2
DOI :
10.1109/ISSPIT.2011.6151533
